An additional challenge presented by this dataset, consistent with many real-world computer vision tasks, is the heterogeneity in target object density (Figure REF B). Images contained between zero and 300 footprints, with substantial coverage throughout that range. This variability presents a challenge to object detection algorithms, which often require estimation of the number of features per image [1]}. Segmentation and object detection of dense or variable density objects is challenging, making this an ideal dataset to test the limits of algorithms' performance.
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